Modified Cascaded Inverter using ANFIS Controller with Reduced Number of Switches
Kola Muralikumar1, Ponnambalam. P2
1Kola Muralikumar, School of Electrical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
2Ponnambalam.P*, School of Electrical Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India.
Manuscript received on November 12, 2019. | Revised Manuscript received on 24 November, 2019. | Manuscript published on December 10, 2019. | PP: 572-578 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6525129219/2019©BEIESP | DOI: 10.35940/ijitee.B6525.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) is proposed to the multilevel inverter to eliminate the Total Harmonic Distortions (THD) with a modified cascaded inverter. This method prohibits the variations presents in the output voltage of the modified cascaded inverter. The work is directed to prove that the importance of ANFIS is integrated learning for alteration of learning content affording to learners desires. The concert of the ANFIS model was calculated by means of standard error quantities which shows the ideal setting needed for better certainty. The MATLAB Simulink performance point out that it is affordable and easy to implement the performance of the ANFIS process. The study of different modified cascaded inverter consisting of five-level, seven-level, and nine- level is carried out for evaluating the THD with ANFIS controller and without ANFIS controller is implemented. The learning outcomes are based on the study of various system settings; it demonstrates the usability of the m-learning application. However, it must be noted that the number of inputs increased being considered by the model increases the system response time of the system.
Keywords: Multilevel Inverters, Cascaded Multilevel Inverter, Adaptive Neuro Fuzzy Inference System, Total Harmonic Distortion, Root Mean Square Value.
Scope of the Article: Fuzzy Logics